/graphify
Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent
Claude Code
$ npx -y skills add Vit129/agy-plugin-cc --skill graphify --agent claude-code
Codex
$ npx skills add Vit129/agy-plugin-cc --skill graphify -a codex -y
Cursor
$ npx skills add Vit129/agy-plugin-cc --skill graphify -a cursor -y
Gemini CLI
$ npx skills add Vit129/agy-plugin-cc --skill graphify -a gemini-cli -y
GitHub Copilot
$ npx skills add Vit129/agy-plugin-cc --skill graphify -a github-copilot -y
OpenCode
$ npx skills add Vit129/agy-plugin-cc --skill graphify -a opencode -y
Windsurf
$ npx skills add Vit129/agy-plugin-cc --skill graphify -a windsurf -y
SKILL.md
graphify.SKILL.mdname: graphify
description: "Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools."
/graphify
Turn any folder of files into a navigable knowledge graph with community detection, an honest audit trail, and three outputs: interactive HTML, GraphRAG-ready JSON, and a plain-language GRAPH_REPORT.md.
Usage
/graphify # full pipeline on current directory
/graphify <path> # full pipeline on specific path
/graphify https://github.com/<owner>/<repo> # clone repo then run full pipeline on it
/graphify https://github.com/<owner>/<repo> --branch <branch> # clone a specific branch
/graphify <url1> <url2> ... # clone multiple repos, build each, merge into one cross-repo graph
/graphify <path> --mode deep # thorough extraction, richer INFERRED edges
/graphify <path> --update # incremental - re-extract only new/changed files
/graphify <path> --directed # build directed graph (preserves edge direction: source→target)
/graphify <path> --whisper-model medium # use a larger Whisper model for better transcription accuracy
/graphify <path> --cluster-only # rerun clustering on existing graph
/graphify <path> --no-viz # skip visualization, just report + JSON
/graphify <path> --html # (HTML is generated by default - this flag is a no-op)
/graphify <path> --svg # also export graph.svg (embeds in Notion, GitHub)
/graphify <path> --graphml # export graph.graphml (Gephi, yEd)
/graphify <path> --neo4j # generate graphify-out/cypher.txt for Neo4j
/graphify <path> --neo4j-push bolt://localhost:7687 # push directly to Neo4j
/graphify <path> --falkordb # generate graphify-out/cypher.txt for FalkorDB
/graphify <path> --falkordb-push falkordb://localhost:6379 # push directly to FalkorDB
/graphify <path> --mcp # start MCP stdio server for agent access
/graphify <path> --watch # watch folder, auto-rebuild on code changes (no LLM needed)
/graphify <path> --wiki # build agent-crawlable wiki (index.md + one article per community)
/graphify add <url> # fetch URL, save to ./raw, update graph
/graphify add <url> --author "Name" # tag who wrote it
/graphify add <url> --contributor "Name" # tag who added it to the corpus
/graphify query "<question>" # BFS traversal - broad context
/graphify query "<question>" --dfs # DFS - trace a specific path
/graphify query "<question>" --budget 1500 # cap answer at N tokens
/graphify path "AuthModule" "Database" # shortest path between two concepts
/graphify explain "SwinTransformer" # plain-language explanation of a node
What graphify is for
Drop any folder of code, docs, papers, images, or video into graphify and get a queryable knowledge graph. Persistent across sessions, honest audit trail (EXTRACTED/INFERRED/AMBIGUOUS), community detection surfaces cross-document connections you wouldn't think to ask about.
What You Must Do When Invoked
If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
**Fast path — existing graph:** Before doing anything else, check whether `graphify-out/graph.json` exists. The expected location is `graphify-out/graph.json` relative to the **current working directory** (i.e. the project root where you are running commands). If it exists AND the user's request is a natural-language question about the codebase (e.g. "How does X work?", "What calls Y?", "Trace the data flow through Z") and NOT an explicit rebuild command (`--update`, `--cluster-only`, or a bare path/URL that implies fresh extraction): **skip Steps 1–5 entirely and jump straight to `## For /graphify query`.** Run `graphify query "<question>"` immediately. Do not run detect. Do not check corpus size. Do not ask the user to narrow. The graph is already built — use it.
If no path was given, use `.` (current directory). Do not ask the user for a path.
If the path argument starts with `https://github.com/` or `http://github.com/`, treat it as a GitHub URL - run Step 0 before anything else, then continue with the resolved local path.
Follow these steps in order. Do not skip steps.
Step 0 - GitHub repos and multi-path merge (only if a URL or several paths)
Only when the path is one or more `https://github.com/...` URLs, or several local subfolders to merge. See `references/github-and-merge.md` for the clone, cross-repo merge, and monorepo flow, then continue with the resolved local path. A plain local path skips this step.
Step 1 - Ensure graphify is installed
# Detect the correct Python interpreter (handles uv tool, pipx, venv, system installs)
PYTHON=""
GRAPHIFY_BIN=$(which graphify 2>/dev/null)
# 1. uv tool installs — most reliable on modern Mac/Linux
if [ -z "$PYTHON" ] && command -v uv >/dev/null 2>&1; then
_UV_PY=$(uv tool run graphifyy python -c "import sys; print(sys.executable)" 2>/dev/null)
if [ -n "$_UV_PY" ]; then PYTHON="$_UV_PY"; fi
fi
# 2. Read shebang from graphify binary (pipx and dirRead more
name: graphify description: "Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools."
/graphify
Turn any folder of files into a navigable knowledge graph with community detection, an honest audit trail, and three outputs: interactive HTML, GraphRAG-ready JSON, and a plain-language GRAPH_REPORT.md.
Usage
/graphify # full pipeline on current directory /graphify <path> # full pipeline on specific path /graphify https://github.com/<owner>/<repo> # clone repo then run full pipeline on it /graphify https://github.com/<owner>/<repo> --branch <branch> # clone a specific branch /graphify <url1> <url2> ... # clone multiple repos, build each, merge into one cross-repo graph /graphify <path> --mode deep # thorough extraction, richer INFERRED edges /graphify <path> --update # incremental - re-extract only new/changed files /graphify <path> --directed # build directed graph (preserves edge direction: source→target) /graphify <path> --whisper-model medium # use a larger Whisper model for better transcription accuracy /graphify <path> --cluster-only # rerun clustering on existing graph /graphify <path> --no-viz # skip visualization, just report + JSON /graphify <path> --html # (HTML is generated by default - this flag is a no-op) /graphify <path> --svg # also export graph.svg (embeds in Notion, GitHub) /graphify <path> --graphml # export graph.graphml (Gephi, yEd) /graphify <path> --neo4j # generate graphify-out/cypher.txt for Neo4j /graphify <path> --neo4j-push bolt://localhost:7687 # push directly to Neo4j /graphify <path> --falkordb # generate graphify-out/cypher.txt for FalkorDB /graphify <path> --falkordb-push falkordb://localhost:6379 # push directly to FalkorDB /graphify <path> --mcp # start MCP stdio server for agent access /graphify <path> --watch # watch folder, auto-rebuild on code changes (no LLM needed) /graphify <path> --wiki # build agent-crawlable wiki (index.md + one article per community) /graphify add <url> # fetch URL, save to ./raw, update graph /graphify add <url> --author "Name" # tag who wrote it /graphify add <url> --contributor "Name" # tag who added it to the corpus /graphify query "<question>" # BFS traversal - broad context /graphify query "<question>" --dfs # DFS - trace a specific path /graphify query "<question>" --budget 1500 # cap answer at N tokens /graphify path "AuthModule" "Database" # shortest path between two concepts /graphify explain "SwinTransformer" # plain-language explanation of a node
What graphify is for
Drop any folder of code, docs, papers, images, or video into graphify and get a queryable knowledge graph. Persistent across sessions, honest audit trail (EXTRACTED/INFERRED/AMBIGUOUS), community detection surfaces cross-document connections you wouldn't think to ask about.
What You Must Do When Invoked
If the user invoked `/graphify --help` or `/graphify -h` (with no other arguments), print the contents of the `## Usage` section above verbatim and stop. Do not run any commands, do not detect files, do not default the path to `.`. Just print the Usage block and return.
**Fast path — existing graph:** Before doing anything else, check whether `graphify-out/graph.json` exists. The expected location is `graphify-out/graph.json` relative to the **current working directory** (i.e. the project root where you are running commands). If it exists AND the user's request is a natural-language question about the codebase (e.g. "How does X work?", "What calls Y?", "Trace the data flow through Z") and NOT an explicit rebuild command (`--update`, `--cluster-only`, or a bare path/URL that implies fresh extraction): **skip Steps 1–5 entirely and jump straight to `## For /graphify query`.** Run `graphify query "<question>"` immediately. Do not run detect. Do not check corpus size. Do not ask the user to narrow. The graph is already built — use it.
If no path was given, use `.` (current directory). Do not ask the user for a path.
If the path argument starts with `https://github.com/` or `http://github.com/`, treat it as a GitHub URL - run Step 0 before anything else, then continue with the resolved local path.
Follow these steps in order. Do not skip steps.
Step 0 - GitHub repos and multi-path merge (only if a URL or several paths)
Only when the path is one or more `https://github.com/...` URLs, or several local subfolders to merge. See `references/github-and-merge.md` for the clone, cross-repo merge, and monorepo flow, then continue with the resolved local path. A plain local path skips this step.
Step 1 - Ensure graphify is installed
# Detect the correct Python interpreter (handles uv tool, pipx, venv, system installs)
PYTHON=""
GRAPHIFY_BIN=$(which graphify 2>/dev/null)
# 1. uv tool installs — most reliable on modern Mac/Linux
if [ -z "$PYTHON" ] && command -v uv >/dev/null 2>&1; then
_UV_PY=$(uv tool run graphifyy python -c "import sys; print(sys.executable)" 2>/dev/null)
if [ -n "$_UV_PY" ]; then PYTHON="$_UV_PY"; fi
fi
# 2. Read shebang from graphify binary (pipx and dirUnofficial community project. Not affiliated with, sponsored or endorsed by Google. "Antigravity" and "Google" are trademarks of Google LLC.
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Questions about graphify.
- Which coding agents can use graphify?
- graphify installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

